Faculty Members

Dr.Haya Mohammad Abdulaziz Alaskar

Associate Professor Department of Computer Sciences College of Computer Engineering & Sciences

Kharj
011-588-8810
h.alaskar@psau.edu.sa

Curriculum Vitae
Publications

Publications

H Alaskar, AJ Hussain, W Khan, H Tawfik, P Trevorrow, P Liatsis, Z Sbaï (2020) data
science approach for reliable classification of neuro-degenerative diseases using gait ,
Journal of Reliable Intelligent Environments, 1-15
Khan, A Hussain, K Kuru, H Al-Askar, (2020)Pupil Localisation and Eye Centre
Estimation Using Machine Learning and Computer Vision, Sensor
Ahmed, Z., Hussain, A., Khan, W., Baker, T., Al-Askar, H., Lunn, J., Liatsis, P., Al-Jumeily,
D., Al-Shabandar, R., (2020). Lossy and Lossless Video Frame Compression: A Novel
Approach for the High-Temporal Video Data Analytics. Remote Sensing, ISI, Scopus.
M IoT-Enabled Flood Severity Prediction via Ensemble Machine Learning Models
Khalaf, H Alaskar, AJ Hussain, T Baker, Z Maamar, R Buyya, P Liatsis,IEEE Access 8,
70375-70386
A Abdullahi, K Bawazeer, S Alotaibai, E Almoaither, M Al-Otaibi, H, alaskar,Pretrained
Convolutional Neural Networks for Cancer Genome Classification,3rd International
Conference on Computer Applications & Information
A Robust Quasi-Quantum Walks-Based Steganography Protocol for Secure Transmission
of Images on Cloud-Based E-healthcare Platforms
B Abd-El-Atty, AM Iliyasu, H Alaskar, A El-Latif, A Ahmed
Sensors 20 (11), 3108.
W Khan, A Hussain, H Alaskar, T Baker, F Ghali, D Al-Jumeily, 2020, Prediction of
Flood Severity Level Via Processing IoT Sensor Data Using Data Science Approach,
IEEE Internet of Things Magazine
H Alaskar, T Vaiyapuri, Z Sbai, 2019, Twitter Analytics for Discovering Socially
Important Locations for Business Improvement, IEEE International Symposium on Signal
Processing and Information …
Alaskar, H., (2019). High Predictive Performance of Dynamic Neural Network Models
for Forecasting Financial Time Series, ISI, Scopus.
Alaskar H., Alzhrani N., Hussain A., Almarshed F. (2019) The Implementation of
Pretrained AlexNet on PCG Classification. In: Huang DS., Huang ZK., Hussain A. (eds)
Intelligent Computing Methodologies. ICIC 2019. Lecture Notes in Computer Science,
vol 11645. Springer, Cham. ISI, Scopus.
Haya Alaskar, A. Hussain, Nourah Alaseem, Panos Liatsis, Dhiya Al-Jumeily:
Application of Convolutional Neural Networks for Automated Ulcer Detection in
Wireless Capsule Endoscopy Images. Sensors 19(6): 1265 (2019). ISI, Scopus. IF: 3.031.
H.Alaskar, 2018 Deep Learning-Based Model Architecture for Time-Frequency Images
Analysis, International Journal of Advanced Computer Science and Applications. ISI,
Scopus.
H. Alaskar, 2018, Deep Learning of EMG Time Frequency Representations for
Identifying Normal and Aggressive Actions, International Journal of Computer Science
and Network Security, Vol. 18 No. 12 pp. 16-25,
http://paper.ijcsns.org/07_book/201812/20181203.pdf. ISI
H. Alaskar, A. Hussain, 2018 ,Prediction of Parkinson Disease Using Gait Signals,
Eleventh International Conference on Developments in e-Systems Engineering, IEEE.ISI
Haya Alaskar , Convolutional Neural Network Application in Biomedical Signals, Journal
of Computer Science and Information Technology, American Research Institute, 2018,
Vol. 6, No. 2, pp. 45-59.
H. Tawfik, H. Alaskar, P. Liatsis, M. khalaf , 2018:A Dynamic Neural Network
Architecture with immunology Inspired Optimization for
Weather Data Forecasting , Big Data Research. ISSN 2214-5796 . ISI, Scopus.
IF:2.952
H. Alaskar, A. Hussain, Data Mining to Support the Discrimination of Amyo-trophic
lateral sclerosis Diseases Based on Gait Analysis In: Huang DS., Gromiha M., Han K.,
Hussain A. (eds) Intelligent Computing Methodologies. ICIC 2018. Lecture Notes in
Computer Science, vol 10956. Online ISBN 978-3-319-95957-3, DOI
https://doi.org/10.1007/978-3-319-95957-3_80, ISI, Scopus.
H. Alasker , S. Alharkan, W. Alharkan ; A. Zaki ; L. Septem Riza,
2017,Detection of kidney disease using various intelligent classifiers, Science in
Information Technology (ICSITech), 2017 3rd International Conference . IEEE
explore.
H. Alasker , A. Zaki , 2017Early Prediction of Chronic Kidney Disease Using Multiple
Automated Techniques, International Journal of Computing & Information Sciences
M. Khalaf, D. Al-Jumeily, R. Keight, R. Keenan, P. Fergus, H. Al-Askar, A. Shaw, I.
Idowu :Training Neural Networks as Experimental Models: Classifying Biomedical
Datasets for Sickle Cell, In: Huang DS., Bevilacqua V., Premaratne P. (eds) Intelligent
Computing Theories and Application. ICIC 2016. Lecture Notes in Computer Science,
vol 9771. Springer, Cham, Online ISBN 978-3-319-42291-6. DOI
https://doi.org/10.1007/978-3-319-42291-6_78 , ISI, Scopus. IF : 0.402
C. Montañez, P. Fergus, D. Al-Jumeily, B. Abdulaimma, H. Al-Askar :A Genetic
Analytics Approach for Risk Variant Identification to Support Intervention Strategies for
People Susceptible to Polygenic Obesity and Overweight. In: Huang DS., Bevilacqua V.,
Premaratne P. (eds) Intelligent Computing Theories and Application. ICIC 2016. Lecture
Notes in Computer Science, vol 9771. Springer, Cham, Online ISBN 978-3-319-42291-6 ,
DOI https://doi.org/10.1007/978-3-319-42291-6_80, ISI, Scopus.IF : 0.402
Al Kafri, S. Sudirman, P. Fergus, D. Al-Jumeily, M. Al-Jumaily, H. Al-Askar, A
Framework on a Computer Assisted and Systematic Methodology for Detection of
Chronic Lower Back Pain Using Artificial Intelligence and Computer Graphics
Technologies. . ICIC 2016. Lecture Notes in Computer Science, Springer, Cham. ISI,
Scopus. IF : 0.402
A.Hussain, D.Al-Jumeily, H. Al-Askar, N. Radi:
Regularized dynamic self-organized neural network inspired by the immune
algorithm for financial time series prediction. Neurocomputing 188: 23-30 (2016).
ISI, Scopus. IF: 3.317.
H. Alaskar, D. J. Lamb, A. Hussain, D. Al-Jumeily, M. Randles, P. Fergus:
Predicting financial time series data using artificial immune system-inspired neural
networks. IJAISC 5(1): 45-68 (2015)
A. Hussain, P. Fergus, H. Al-Askar, D. Al-Jumeily, F. Jager:
Dynamic neural network architecture inspired by the immune algorithm to predict
preterm deliveries in pregnant women. Neurocomputing 151: 963-974 (2015). ISI,
Scopus. IF: 3.317.
Reid D., Tawfik H., Hussain A.J., Al-Askar H. (2015) Forecasting Weather Signals Using
a Polychronous Spiking Neural Network. In: Huang DS., Bevilacqua V., Premaratne P.
(eds) Intelligent Computing Theories and Methodologies. ICIC 2015. Lecture Notes in
Computer Science, vol 9225. Springer, Cham
A. Hussain, P. Fergus, D. Al-Jumeily, H. Alaskar, N. Radi:
The Utilisation of Dynamic Neural Networks for Medical Data Classifications- Survey
with Case Study. ICIC (3) 2015: 752-758
A. Hussain, D. Al-Jumeily, H. Al-Askar “The Application of Dynamic Self-organised
Multilayer network Inspired by the Immune Algorithm for weather signals forecast”, The
Third International Conference on Technological Advances in Electrical, Electronics and
Computer Engineering, TAEECE 2015, Beirut, Lebanon, 2015.
I. Idowu, Paul Fergus, A. Hussain, Chelsea Dobbins, H. Al-Askar:
Advance Artificial Neural Network Classification Techniques Using EHG for Detecting
Preterm Births. CISIS 2014, IEEE explore, 95-100
Hussain A.J., Al-Askar H., Al-Jumeily D. (2014) Physical Time Series Prediction Using
Dynamic Neural Network Inspired by the Immune Algorithm. In: Bouchachia A. (eds)
Adaptive and Intelligent Systems. ICAIS 2014. Lecture Notes in Computer Science, vol
8779. Springer, Cham
Al-Askar H., Hussain A.J., Al-Jumeily D., Radi N. (2014) Regularized Dynamic Self
Organized Neural Network Inspired by the Immune Algorithm for Financial Time Series
Prediction. In: Huang DS., Han K., Gromiha M. (eds) Intelligent Computing in
Bioinformatics. ICIC 2014. Lecture Notes in Computer Science, vol 8590. Springer,
Cham
Alaskar H., Hussain A.J., Paul F.H., Al-Jumeily D., Tawfik H., Hamdan H. (2014)
Feature Analysis of Uterine Electrohystography Signal Using Dynamic Self-organised
Multilayer Network Inspired by the Immune Algorithm. In: Huang DS., Bevilacqua V.,
Premaratne P. (eds) Intelligent Computing Theory. ICIC 2014. Lecture Notes in
Computer Science, vol 8588. Springer, Cha
Evaluation of Advanced Artificial Neural Network Classification and Feature Extraction
Techniques for Detecting Preterm Births Using EHG Records. In: Huang DS., Han K.,
Gromiha M. (eds) Intelligent Computing in Bioinformatics. ICIC 2014. Lecture Notes in
Computer Science, vol 8590. Springer, Cham
Huang R., Tawfik H., Hussain A.J., Al-Askar H. (2014) The Application of Artificial
Immune Systems for the Prediction of Premature Delivery. In: Huang DS., Jo KH., Wang
L. (eds) Intelligent Computing Methodologies. ICIC 2014. Lecture Notes in Computer
Science, vol 8589. Springer, Cham
D. Al-Jumeily ; A. Hussain ; H. Alaskar (2013) Recurrent neural networks inspired by
artificial Immune algorithm for time series prediction. The 2013 International Joint
Conference on Neural Networks (IJCNN) Dallas, TX, USA: 1-8.
Invited Book Chapters:
“Recurrent Neural Networks in Medical Data Analysis and Classifications”,
in: D. Al-Jumeily, A. Hussain, C. Mallucci, C. Oliver (eds), Applied Computing
in Medicine and Health, Elsevier, 2015.

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Dr.Haya Mohammad Abdulaziz Alaskar

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Faculty Members

Dr.Haya Mohammad Abdulaziz Alaskar

Publications

Administration of Public Relations and Media